Genes · 2020 · 48 citations · 48 references
Life SciencesBioinformaticsMolecular BiologyGene ExpressionGenomicsTranscriptomicsDifferential Expression AnalysisDifferential Gene Expression AnalysisGene Expression ProfilingNext-generation SequencingRna Sequencing AnalysisTranscriptomic ProfilingDifferential Gene ExpressionDifferential Transcript ExpressionRna Sequencing (Rna-seq)Rna Sequencing Differential Expression AnalysisTechnical Pitfalls
RNA-Seq enables the identification and quantification of RNA molecules, often with the aim of detecting differentially expressed genes (DEGs). Although RNA-Seq evolved into a standard technique, there is no universal gold standard for these data’s computational analysis. On top of that, previous studies proved the irreproducibility of RNA-Seq studies. Here, we present a portable, scalable, and parallelizable Nextflow RNA-Seq pipeline to detect DEGs, which assures a high level of reproducibility. The pipeline automatically takes care of common pitfalls, such as ribosomal RNA removal and low abundance gene filtering. Apart from various visualizations for the DEG results, we incorporated downstream pathway analysis for common species as Homo sapiens and Mus musculus. We evaluated the DEG detection functionality while using qRT-PCR data serving as a reference and observed a very high correlation of the logarithmized gene expression fold changes.
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fastp: an ultra-fast all-in-one FASTQ preprocessor
Shifu Chen, Yanqing Zhou, Yaru Chen et al. · Bioinformatics · 2018 · 29.7K citations · Full text